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Record W2159225887 · doi:10.1139/z10-043

How to build a pectoral fin: functional morphology and steady swimming kinematics of the spotted ratfish (<i>Hydrolagus colliei</i>)

2010· article· en· W2159225887 on OpenAlexaffvenue
Kathleen Lois Foster, Timothy E. Higham

Bibliographic record

VenueCanadian Journal of Zoology · 2010
Typearticle
Languageen
FieldEngineering
TopicBiomimetic flight and propulsion mechanisms
Canadian institutionsUniversity of British Columbia
FundersForskningsrådet om Hälsa, Arbetsliv och VälfärdClemson University
KeywordsBiologyFish finAnatomyChondrichthyesAdductor musclesZoologyFisheryFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Aquatic flight is the primary locomotor mode for many animals, including penguins and other diving birds, turtles, and fishes, where labriform and rajiform swimming have been the focus of much interest. However, despite its interesting phylogenetic placement, little is known about the aquatic flight of the sister lineage to the elasmobranchs, the chimaerids. This study investigates the pectoral fin morphology of the spotted ratfish ( Hydrolagus colliei (Lay and Bennett, 1839)) as a possible factor underlying the kinematics of their steady swimming by comparing muscle mass, distribution, and abductor to adductor ratio with those of a closely related shark ( Squalus acanthias L., 1758). Despite fundamental differences in swimming mode, abductor to adductor muscle ratio did not differ between species (P = 0.49). However, the muscle ratio in the spotted ratfish was similar to the range determined in other flapping labriform swimmers. Ratfish had larger, distally placed pectoral fin muscles relative to body size than dogfish (P &lt; 0.0001) possibly aiding in fine control. Stroke amplitude remained constant across body size (P = 0.26) and relative swimming speed (P = 0.23) in the ratfish, whereas the downstroke was significantly faster than the upstroke (P = 0.006). The similar muscle ratio, despite differences in stroke phases, may be explained by physiological or in vivo recruitment differences between abductors and adductors in the ratfish.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.705
Threshold uncertainty score0.586

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.179
Teacher spread0.170 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations9
Published2010
Admission routes2
Has abstractyes

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